Over the last several years, massively parallel sequencing platforms have reduced the cost-per-base of DNA sequencing by several orders of magnitude (Shendure & Ji 2008). Of the “next-generation” technologies that are commercially available, nearly all rely on iterative cycles of biochemistry and imaging of dense arrays of sequencing features to generate relatively short reads, i.e. “cyclic-array” methods (Shendure et al. 2005; Margulies et al. 2005; Drmanac et al. 2009; Braslaysky et al. 2003; Bentley et al. 2008). The broad dissemination of these platforms represents the culmination of decades of effort to develop practical alternatives to electrophoretic sequencing (Shendure et al. 2004).
In the context of this success, many developing technologies have the potential to improve the technical capability of what is already feasible today. Such improvements may be accomplished by further development of cyclic array methods, or through the maturation of other promising strategies such as nanopore sequencing (Branton et al. 2008), real-time observation of DNA synthesis (Eid et al. 2009) and sequencing by electron microscopy. Massively parallel sequencing platforms have also given rise to several types of sequencing applications, including resequencing, de novo assembly, exome sequencing (Ng et al. 2009), RNA-Seq (Mortazavi et al. 2008), ChIP-Seq (Johnson et al. 2007), and genome-wide chromatin interaction mapping (Lieberman-Aiden et al. 2009; Duan et al. 2010).
Although DNA sequencing technology platforms have improved at a rapid pace, the cost of DNA sequencing remains prohibitive for some goals. Therefore, it is desired to produce methods related to DNA sequencing technology that not only improve the application of existing and developing technology, but also reduce the cost.